There are a wide variety of situations where determinations are made at different points through the course of a process and/or where determinations are made based on different data. Such determinations may vary by the particular type of data that is used in the determination. Alternatively, such determinations may involve data that is secured at a different time, i.e., updated data may be used (instead of older data that was used in a prior determination). A determination might be expressed in terms of a score, i.e., some other quantitative representation.
As can be appreciated, such different determinations made over a period of time or made based on different data may vary in the result such determinations yield. For example, a credit card issuer may be conducting a campaign to secure new credit card customers. The campaign might typically involve determining individuals that should be mailed credit card offers. In determining such individuals, the credit card issuer generates a credit risk score for each individual. The credit risk score may be based on data secured from a credit bureau or other data that is assessable by the credit card issuer. At this point in the process, the credit risk score might be characterized as a “front end” risk score. In other words, at actual mailing selection time, the credit card issuer has to select names for offers from the whole credit eligible universe.
Individuals who receive the offer (through mailings, e-mailings, or any other suitable medium) have the opportunity to review and accept the offer. Accordingly, at some later time, the credit card issuer will receive responses from some of those individuals.
Once a response is received from an individual (a respondent), the credit card issuer then determines whether the credit card issuer will indeed issue a credit card to the respondent. In other words, at credit approval/decline time, the business has to make the booking decision among all of respondent applicants. This decision involves determination of a further risk score, i.e., a “back-end” risk. The back-end risk score will thus be determined at a later time, than the front end risk-score, and might also involve different parameters. As a result, it is very likely the back-end risk score is different from the one based on the random sample of the whole eligible credit universe, i.e., different from the front end risk score.
In such situation, the credit card issuer, as between the front-end risk score and the back-end risk score, has two different universes and two different goals. Using known techniques, it is very difficult to provide satisfactory results for one goal while it is developed against another goal. Historically business uses two different scores, one for the front end determination and one for the back end determination. However, that approach sometimes causes problems since the credit card issuer or other business makes the selection decision to mail an offer based on one score, and later the business decides to decline a responder of the offer based on second score. Such action is unfortunately sometimes necessary, from a business perspective, but is not beneficial to the business from a public relations perspective.
The above and other problems are present in known processes.